The Set Covering Problem (SCP) is a classic problem in combinatorial optimization. SCP has many applications in engineering, including problems involving routing, scheduling, stock cutting, electoral redistricting and others important real life situations. Because of its importance, SCP has attracted attention of many researchers. However, SCP instances are known as complex and generally NP-hard problems. Due to the combinatorial nature of this problem, during the last decades, several metaheuristics have been applied to obtain efficient solutions. This paper presents a metaheuristics comparison for the SCP. Three recent nature-inspired metaheuristics are considered: Shuffled Frog Leaping, Firefly and Fruit Fly algorithms. The results show that they can obtainn optimal or close to optimal solutions at low computational cost.